ALTERNATIF KEBIJAKAN REHABILITASI DAERAH ALIRAN SUNGAI (DAS) MENGGUNAKAN TEKNOLOGI DATA MINING - Fahmi, Muhammad Farid (Masyarakat Telematika Dan Informasi : Jurnal Penelitian Teknologi Informasi dan Komunikasi, 2016)
The success rate of rehabilitation of the watershed is still not maximum, one reason is the lack of information that could help in the rehabilitation of the watershed. From the above problems, we need a study to provide a reference or any other alternative in determining priority watersheds to be rehabilitated, one through data mining technology. In this study watershed will be clustered using K-means clustering algorithm based on parameter characteristics. Trial in Tondano watershed found that the watershed in cluster 1 and 3 are critical watershed compared to the other groups. The trial results also showed that the process is not much different clustering or 90.64% when compared to the same watershed calculations manually so that it can be used as a reference stau other alternatives in policy and planning for watershed rehabilitation.